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Global warming, as many other threats, requires more activity from the government, and people inquire about this, rightfully so. However, the public and private sectors nowadays have a joint responsibility with society. Global warming has come out of the scientific community and shows that climate change is an important social, economic, and political issue. Currently the carbon dioxide (CO 2 ) emissions by transportation sector are the main polluter of the planet. For this reason, in this paper we propose a reflection on transport, which is an important sector of the economy, responsible for the generation of many jobs and wealth but, at the same time, it has negative impacts on people, companies, and the environment. Recent investigations demonstrate that mobility problems affects the life quality of the people, business productivity and gross domestic product (GDP) performance. In the face of the changes that we are experiencing, it is important to find alternatives that assistance governments in the decision-making to solve the problem of traffic in large and medium-size cities and bring well-being to the population. The goal is to provide accurate tool to help take the best decisions in situations that most of the time has a lack of economic resources and transparency. Another motivation is to increase the productivity of companies and achieve sustainable development by reducing mobility problems and CO 2 emissions. As outcomes of the paper, an in-depth study is presented on the subject that indicates a gap in the literature with fuzzy logic applied to sustainability. We indicate a sustainable option for the transport sector using algorithms for decision-making, and broaden the discussion on climate change and solutions to reduce the impacts caused by humanity. When the models were applied through a conceptual study, it was possible to provide an instrument generated on the use of algorithms that can aid decision-making by getting qualitative data from a discussion with stakeholders on a topic. Finally, the document identifies the importance of the participation of stakeholder, reinforces legitimacy and transparency in decision-making processes and above all present a tool that can help governments to solve this problem. In short, this work proposes an original and valuable tool to be applied in the decision-making process for the sustainable transport sector based on the stakeholder engagement. [ABSTRACT FROM AUTHOR]

The mass production companies need to seek high efficiency in the use of equipment and human resources, as well as in the consumption of their inputs. One of the key methods to address these challenges is the adoption of Overall Equipment Effectiveness, derived from Total Productive Maintenance. This work aims to propose a new efficiency indicator, called Overall Machinery Effectiveness, to be applied in an automotive company in Brazil that adopted Overall Equipment Effectiveness indicator. The studied company made available production data from ten months, associated to two Press machines, generating twenty Decision Making Units for Data Envelopment Analysis and Bi-Objective Multiple Criteria Data Envelopment Analysis models application. As results, Press #2 was identified as being the most critical because, among the first ten DMUs in the efficiency ranking, seven are associated to Press #1. The targets values recommended by the new indicator were considered feasible to be implemented by the company, thus validating in practice the new proposed procedure for the management of machines effectiveness. Moreover, the identification of the relevant variables (input and output) for the Press #1, and Press #2, allowed the decision maker to act in the best way to increase their efficiency. [ABSTRACT FROM AUTHOR]

Ruptures and interruptions in supply chains (SC) can cause large financial losses and undermine the reputation of firms. In this respect, there is growing interest among researchers in the theme of supply chain risk management (SCRM). SCRM involves analysis carried out in various steps. However, researchers diverge over the number and content of these steps. In light of this problem, the aim of the present study was to analyze whether it is possible to apply the ISO 31000 standard as a systematic procedure for SCRM. And, if so, how the standard can be implemented in the SCRM context, as a framework in a specific company. Through a systematic literature review, we compared and harmonized the risk management steps proposed by researches about SCRM. Additionally we developed a pathway to identify and prioritize which ISO 31000:2009 risk assessment tools and techniques are supposed to integrate a procedure for SCRM, based on the Analytic Hierarchy Process (AHP), exemplified in an automotive supply chain. Based on the research findings, we infer that ISO 31000 can be used beneficially as a standardized method to perform SCRM, as long as tools and techniques are selected according to the company needs and business characteristics. [ABSTRACT FROM AUTHOR]

A comparative study was used to outline the literature in the research topic. This paper aims to present a bibliometric study ofmulti-criteria decision-making methods most applied in publications from 1990 to 2014. Our research presented relations of papers published in the Web of Science Core Collection, regarding the following keywords Analytic Hierarchy Process and Supply Chain. The research evidenced that the Analytic Hierarchy Process has been the method mostapplied in publications from 1993. It also showed the analysis of the predecessor and successor citation network for the selected publications under topics as supplier selection, supply development, performance measurement and value chain through the CitNetExplore software. [ABSTRACT FROM AUTHOR]

In August 2010, it was sanctioned a National Solid Waste Policy (PNRS - Política Nacional de Resíduos Sólidos) that features innovations as the Reverse Logistics which determines that manufacturers, importers, distributors and retailers must perform the collection of used packaging. Thus, what is the actual difficulty of companies in meeting the requirements of the PNRS? The purpose of this article is to propose a management model that uses Information and Communication Technology (ICT) and the WEB to assist in the integration of all stages of Supply Chains of electronic products and their components. It is an applied research with a qualitative approach where, after a critical analysis of the PNRS, a literature review was conducted involving the state of the art in Supply Chain Management, the ICT and the development of Enterprise Resource Planning (ERP) systems. The application of the proposed model in supply chains of electronic appliances through environmental protection and a direct interaction with the ultimate consumer offers enterprises a competitive advantage and can minimize financial losses associated with fines and violations. The following stages of this research include the development of a WEB portal with the proposed model and its availability for government use, thus enabling its practical application trials. [ABSTRACT FROM AUTHOR]

In this paper a new revised multi-choice goal programming (RMCGP-LHS) model is proposed to deal with uncertainty in sugar cane harvest scheduling for sugar and ethanol milling companies. The RMCGP-LHS model uses a weekly decision-making horizon and takes into account the time and condition of land management, cane cutting decisions, and agricultural logistics. Its objective is to obtain information in order to harvest sugar cane plots in the period closest to the highest saccharose levels, while also minimizing agro-industrial costs. The RMCGP-LHS model was applied to a real case sugar and ethanol mill, and its optimization has provided harvesting policies that were validated by the company’s managers. Besides that the RMCGP-LHS model is a very practical tool for simulating in a fast way different scenarios involving uncertainties on model parameters and helping the managers in decision making process in real time. [ABSTRACT FROM AUTHOR]

• A method was developed to reduce the search space in simulation optimization. • The method combines orthogonal Arrays, data envelopment analysis and optimization. • The method reduces the search space in various case studies by roughly 97%. • The method defines the best range of variation for each decision variable. • The method is applied to simulation optimization with a single objective. This article proposes a new combination of methods to increase optimization simulation efficiency and reliability, utilizing orthogonal arrays, fuzzy-data envelopment analysis (FDEA) with linear membership function, and discrete event simulation (DES). Considering a simulation optimization problem, experimental matrices are generated using orthogonal arrays and which simulation runs (scenarios) will be executed are defined, followed by FDEA to analyze and rank the scenarios in terms of their efficiency (considering occurrence of uncertainty). In this way, it is possible to reduce the search space of scenarios to be simulated, and avoid the need for replications in DES, without impairing the quality of the final solution. Six real cases that were solved by the proposed approach are presented. In order to highlight the efficiency of the proposed method, in Cases 5 and 6, all viable solutions of each of these problems were tested, ie, 100% of the search space was analyzed, and it was found that the solution obtained by the new method was statistically equal to the overall optimal solution. Note that for the other real cases solved, the solutions obtained by the proposed method were also statistically equal to those obtained from the original search space, and that analyzing 100% of the viable solutions space would be computationally impossible or impractical. These results confirmed the reliability and applicability of the proposed method, since it enabled a significant reduction in the search space for the simulation application compared to conventional simulation optimization techniques. [ABSTRACT FROM AUTHOR]

• A Goal Programming model to optimize a waste paper recycling network was elaborated. • The model considers objectives related to sustainability, multiple products and periods. • Vehicle routing, different-capacity vehicles and multiple trips are highlights. • The possibility of storing material at the collection points is considered. • The formulation provides relevant solutions to assist decision-makers. Organization and planning of reverse logistics networks make sustainable processes more efficient. Thus, an important sector for connecting the collection and waste paper recycling echelons is the intermediate center. In this study, a Mixed Integer Linear Programming model, which is multi-objective, multi-product, multi-level and multi-period, was developed to optimize the waste paper logistics processes of intermediate centers. The formulation includes the following echelons: collection, considering vehicle routing with different capacities; inventory of non-baling materials; baling sorted waste and inventory of bales; selling bales; disposal of non-recyclable waste. The aims of the model include: maximizing the collected waste; minimizing distances; maximizing both the production and sale of bales, and minimizing costs. According to research carried out in the literature, the developed model is a new proposal and to implement it, the Weighted Goal Programming and Revised Multi-Choice Goal Programming approaches were used to deal with multiple objectives and incorporate uncertainty into the quantity of waste available for collection. To analyze the proposed model, computational tests were executed with instances based on real data from a Brazilian company in the sector. For all performed tests, General Algebraic Modeling System 23.6.5 modeling language and CPLEX 12.2.0.2 solver were used for modeling and optimization. The results show that this study presents formulation and technological approaches that represent real situations and provide competitive solutions to the problem. [ABSTRACT FROM AUTHOR]

Among the most frequently used experimental design techniques is the response surface methodology (RSM), which uses an approximation of the real objective function, in the form of an empirical quadratic function. RSM allows the identification of the relations between independent variables (or factors) and a (dependent) response variable. The main contribution of this article is to propose a new procedure that considers the insertion of uncertainties in the coefficients of this empirical function, which is what generally occurs, in practical experimental problems. The new procedure was applied to a real case related to a stamping process in an automotive company, and the results were compared to those obtained by applying classic RSM. The advantages offered by this innovative procedure are presented and discussed, including the statistical validation of the results. The proposed procedure reduces, and sometimes eliminates, the need for additional confirmatory experiments in the laboratory, and allows getting a better adjustment of the factor values and the optimized response variable value compared to the results calculated by classic RSM. It was possible to determine that the proposed procedure outperforms the use of (deterministic) optimization, using the generalized reduced gradient (GRG) algorithm, which is traditionally employed in RSM applications. Unlabelled Image • The advantages by this innovative procedure including the statistical validation • The main contribution is insertion of uncertainties in the objective function. • The new procedure was applied to a real case related to a stamping process. • The results were compared to those obtained by applying classic RSM. [ABSTRACT FROM AUTHOR]

Green Supply Chain Management (GSCM) is an important issue for organizations that spend considerable amounts of investments on personnel training annually. Although these investments present positive effects, the manner to assess the effectiveness of the training is unclear. Training, whose characteristics are intangible, is sometimes difficult to be assessed. This research has carried out a multi-criteria training assessment for GSCM through the four top-level processes of Supply Chain Operations Reference Model (SCOR) i.e., Plan, Source, Make and Deliver. Analytic Hierarchy Process was applied in the training assessment. In the chemical industry where our study was performed, the SCOR top-level processes were considered criteria, whereas Individual and Organizational Benefits alternatives. The modeling considered pairwise judgments for criteria, and ratings or absolute measure for alternatives. The analysis revealed that training essentially contributes to the organization, resulting in 87% for Organizational Benefits, and 77% for Individual Benefits. Organizational Benefits focused on the use of the best practices in GSCM and on the common understanding of vocabulary and processes. In addition, Individual Benefits increased knowledge and skills in GSCM. This result, presented to managers of the company, was validated as consistent and feasible. [ABSTRACT FROM AUTHOR]